Comments (5)
you need to go first inside cudamat folder and install it by running "make"
make sure to set correct path to relevant dependencies inside Makefile
let me know if it helped .
I will make relevant changes to documentation
from unsupervised-videos.
Hi Elman,
Thanks, I have solved that problem and it can run now.
Bests,
Chengcheng
On Mon, Mar 14, 2016 at 1:47 AM, Elman Mansimov [email protected]
wrote:
you need to go first inside cudamat folder and install it by running "make"
make sure to set correct path to relevant dependencies inside Makefilelet me know if it helped .
I will make relevant changes to documentation—
Reply to this email directly or view it on GitHub
#4 (comment)
.
Best,
Chengcheng Jia
PhD Student
Electrical and Computer Engineering,
Northeastern University,
Cell: 1-(857)320-9063
Email: [email protected]
Personal Page: https://sites.google.com/site/chengchengjia128/
from unsupervised-videos.
Hi Elman,
I am trying to run my code by using your code, but I did not find the code
to generate feature (like ucf101). Could you share the code to generate
feature please? Thanks a lot.
Bests,
Chengcheng
On Mon, Mar 14, 2016 at 11:32 AM, Elman Mansimov [email protected]
wrote:
—
Reply to this email directly or view it on GitHub
#4 (comment).
Best,
Chengcheng Jia
PhD Student
Electrical and Computer Engineering,
Northeastern University,
Cell: 1-(857)320-9063
Email: [email protected]
Personal Page: https://sites.google.com/site/chengchengjia128/
from unsupervised-videos.
You can use any popular software framework like caffe or Toronto ConvNet software https://github.com/TorontoDeepLearning/convnet in order to extract features.
You can then use lstm_classifier.py to do classification.
from unsupervised-videos.
Hi Elman,
I see. I will do it as suggested. Thanks a lot!
Bests,
Chengcheng
On Wed, Mar 16, 2016 at 1:32 PM, Elman Mansimov [email protected]
wrote:
You can use any popular software framework like caffe or Toronto ConvNet
software https://github.com/TorontoDeepLearning/convnet in order to
extract features.You can then use lstm_classifier.py to do classification.
—
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Reply to this email directly or view it on GitHub
#4 (comment)
Best,
Chengcheng Jia
PhD Student
Electrical and Computer Engineering,
Northeastern University,
Cell: 1-(857)320-9063
Email: [email protected]
Personal Page: https://sites.google.com/site/chengchengjia128/
from unsupervised-videos.
Related Issues (20)
- CUDAMatException HOT 2
- lstm classifier examples
- CUBLAS error HOT 3
- invalid device function{cm.CUDAMatrix.init_random(42)} cudamat.cudamat.CUDAMatException: CUDA error: no error HOT 10
- Weights for frame prediction used in the paper HOT 5
- Questions regarding some design decisions used to train MovingMNIST in the paper HOT 6
- KeyError: "Unable to open object (Object 'lstm_1_enc:w_dense' doesn't exist)"
- Data format HOT 1
- no eps decay? HOT 1
- 1 input -> next predicted output
- Questions about LSTM_classifier HOT 1
- no kernel image is available for execution on the device HOT 2
- runtest failed:[runtest] segmentation fault (core dumped)
- Error while giving the command for training HOT 6
- Extrpolating matrices
- Training with new dataset HOT 1
- Make the file Makefile in the folder cudamat HOT 2
- Request for the script to generate moving mnist video dataset HOT 1
- Videos
- -![image](https://user-images.githubusercontent.com/101527858/159179877-0df83b60-09df-4a31-834b-d59002aba969.jpeg)
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